Yu Fan Chen

21 total papers · 1.4k total citations
13 papers, 691 citations indexed

About

Yu Fan Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Mechanical Engineering. According to data from OpenAlex, Yu Fan Chen has authored 13 papers receiving a total of 691 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Mechanical Engineering. Recurrent topics in Yu Fan Chen's work include Reinforcement Learning in Robotics (6 papers), Robotic Path Planning Algorithms (5 papers) and Bayesian Modeling and Causal Inference (3 papers). Yu Fan Chen is often cited by papers focused on Reinforcement Learning in Robotics (6 papers), Robotic Path Planning Algorithms (5 papers) and Bayesian Modeling and Causal Inference (3 papers). Yu Fan Chen collaborates with scholars based in United States, Australia and France. Yu Fan Chen's co-authors include Jonathan P. How, Michael Everett, Miao Liu, Nazım Kemal Üre, John Vian, Girish Chowdhary, Shayegan Omidshafiei, Ali‐akbar Agha‐mohammadi, Shih‐Yuan Liu and Justin Miller and has published in prestigious journals such as IEEE Access, IEEE Control Systems and Journal of Intelligent & Robotic Systems.

In The Last Decade

Yu Fan Chen

13 papers receiving 660 citations

Hit Papers

Socially aware motion pla... 2017 2026 2020 2023 2017 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Yu Fan Chen 438 287 217 166 135 13 691
Miao Liu 343 0.8× 305 1.1× 172 0.8× 158 1.0× 184 1.4× 33 698
Peter Trautman 332 0.8× 183 0.6× 253 1.2× 203 1.2× 129 1.0× 9 582
Yuejiang Liu 366 0.8× 287 1.0× 216 1.0× 143 0.9× 79 0.6× 10 579
Gonzalo Ferrer 459 1.0× 151 0.5× 195 0.9× 261 1.6× 118 0.9× 42 725
Malika Meghjani 281 0.6× 105 0.4× 326 1.5× 86 0.5× 128 0.9× 30 734
Markus Kuderer 245 0.6× 172 0.6× 284 1.3× 107 0.6× 241 1.8× 11 636
Tingxiang Fan 332 0.8× 186 0.6× 112 0.5× 62 0.4× 122 0.9× 16 563
Joshua Joseph 253 0.6× 196 0.7× 181 0.8× 48 0.3× 122 0.9× 13 573
You Hong Eng 250 0.6× 88 0.3× 364 1.7× 75 0.5× 185 1.4× 13 644
Jérôme Guzzi 432 1.0× 196 0.7× 56 0.3× 72 0.4× 122 0.9× 28 732

Countries citing papers authored by Yu Fan Chen

Since Specialization
Citations

This map shows the geographic impact of Yu Fan Chen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yu Fan Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu Fan Chen more than expected).

Fields of papers citing papers by Yu Fan Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu Fan Chen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yu Fan Chen. The network helps show where Yu Fan Chen may publish in the future.

Co-authorship network of co-authors of Yu Fan Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Fan Chen. A scholar is included among the top collaborators of Yu Fan Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yu Fan Chen. Yu Fan Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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